Water isotopes – climate relationships for the mid-Holocene and pre-industrial period simulated with an isotope-enabled version of MPI-ESM

Abstract

Abstract. We present here the first results, for the pre-industrial and mid-Holocene climatological periods, of the newly developed isotope-enhanced version of the fully coupled Earth system model MPI-ESM, called hereafter MPI-ESM-wiso. The water stable isotopes H216O, H218O and HDO have been implemented into all components of the coupled model setup: the atmosphere model ECHAM6, the land/soil vegetation model JSBACH, and the ocean/sea ice model MPIOM. The exchanges of the related isotope masses between the atmosphere and the ocean are made via the coupler OASIS3. The mid-Holocene, one of the PMIP4-CMIP6 entry cards to evaluate the performance of the latest generation of fully-coupled General Circulation Models, provides the opportunity to evaluate the model response to changes in the seasonal and latitudinal distribution of insolation induced by different orbital forcing conditions. The results of our equilibrium simulations allow to evaluate the performance of the isotopic model in simulating the spatial and temporal variations of water isotopes in the different compartments of the hydrological system for warm climates. It represents a first necessary step before simulating other climatological interglacial periods or transient Holocene experiment. For pre-industrial climate, MPI-ESM-wiso reproduces very well the observed spatial distribution of isotopic content in precipitation, in link with the spatial variations in temperature and precipitation rate. We find also a good model-data agreement with the observed distribution of isotopic composition in surface seawater, but a bias with too depleted surface seawater is present in the Arctic Ocean. All these results are improved compared to the previous model version ECHAM5/MPIOM. The spatial relationships of water isotopic composition with temperature, precipitation rate and salinity are consistent with observational data. For the pre-industrial climate, the interannual relationships of water isotopes with temperature and salinity are globally lower than the spatial ones, consistent with previous studies. Simulated results under mid-Holocene conditions are in fair agreement with the isotopic measurements from ice cores and continental speleothems. MPI-ESM-wiso simulates a depletion in isotopic composition of precipitation from North Africa to the Tibetan plateau via India due to the enhanced monsoons during mid-Holocene. Over Greenland, our simulation indicates enriched isotopic composition of precipitation over Greenland in link with higher summer temperature and reduction in sea ice, shown by positive isotope-temperature gradient. For the Antarctic continent, the model simulates depleted isotopic values over the East Antarctic plateau, in link with the lower temperatures during the mid-Holocene period, while similar or higher isotopic values are modeled over the rest of the continent. While variations of isotopic contents in precipitation over West Antarctica between mid-Holocene and pre-industrial periods are partly controlled by changes in temperature, the transport of relatively enriched water vapor near the coast to the western ice core sites could play a role in the final isotopic composition. The reconstruction of past salinity through isotopic content in sea surface waters can be complicated for regions with strong ocean dynamics, variations in sea ice regimes or significant changes in freshwater budget, giving an extremely variable relationship between isotopic content and salinity of ocean surface waters over small spatial scales. These complicating factors demonstrate the complexity in interpreting water isotopes as past climate signals of warm periods like the mid-Holocene.

Abrupt Climate and Weather Changes Across Time Scales

“…Alternatively, their effects must be parameterized as in current state‐of‐the‐art general circulation models, where the typical horizontal resolutions of the ocean component is about 1°. Practically, given the present high‐performance computer capacities, efficient and parallelized model codes, it is now possible to conduct isotope‐enabled (e.g., Cauquoin et al, 2019; Werner et al, 2018) simulations for 50–100 model years per day even with a multiscale ansatz (Shi et al, 2020).…”

Seasonal reconstructions coupling ice core data and an isotope enabled climate model – implications of seasonality, climate modes and selection of proxy data

“…Speleothem data could potentially also be used, however is a challenge to find high resolution continuous data sets due to growth hiatuses (e.g., de Jong et al, 2013). Newly updated isotope enabled climate models (e.g., Cauquoin et al, 2019) shows the continual development of this field. This makes running new millennium length model simulations attractive for the purpose of providing better sampling pools for finding model analogues to match the proxy data.…”

Contribution to the hydrogeological knowledge of the high mountain karst aquifer of the Port del Comte (SE, Pyrenees)

“…IGCMs provide the isotopic signal distribution of a particular time period along with the corresponding evolution of climate variables, which is particularly useful in paleoclimate and paleo-altimetry studies (Rowley and Garzione, 2007;Bershaw et al, 2012;Gierz et al, 2017;Cauquoin et al, 2019). Besides, these models unravel the complex relationships between geochemical climate proxies (e.g., ice core δ 18 O, tree cellulose δ 18 O, and coral δ 18 O) and climate simulations (Okazaki and Yoshimura, 2019).…”

“…A step ahead was done when climate models were used to reproduce the climate of the past, trying to simulate long complex climate scenarios based on proxy climate information (Braconnot et al, 2012;Lohmann et al, 2013;Pfeiffer and Lohmann, 2016). In this line and more recently, paleoclimate modelling studies have begun to adopt a new strategy by using fully coupled isotope-enabled global climate models (IGCM), allowing them to directly simulate paleoclimate proxies (Sjolte and Hoffmann, 2014;Holloway et al, 2016;Gierz et al, 2017;Cauquoin et al, 2019;Sjolte et al, 2020). Nevertheless, all these models require a direct validation using independent isotopic proxy data.…”